There are several challenges related to the autonomous control of small robotic platforms. The small payload and usually low cost restrict them from carrying accurate, inertial localization systems. Therefore, in GPS denied areas, automatic tasks—like mapping and searching—become a challenge.
Several technologies have been developed to overcome these challenges. Visual odometry and LADAR odometry are commonly used to complement the higher drift of the inertial components, aiding in localization. The problem with these techniques is that they are brittle in some environments; in particular, tunnels, caves, and man-made structures pose some challenges. Poor lighting conditions, low quality cameras, and dusty or smoky conditions further exacerbate the localization errors. For example, state-of-the-art quadrotors equipped with quality cameras, flying in a sufficiently-lit tunnel, while using visual odometry, may achieve 5% to 10% error as a function of distance travelled. This error becomes 10% to 25% of distance travelled if the quad-rotor must carry its own illumination. If the tunnel is dusty or smoky, the error in localization is driven by the inertial components.
The inertial components of the navigation unit are composed of accelerometers and gyroscopes. The position is computed by double integrating the acceleration. Therefore, small bias errors in acceleration become exponential errors in position. If the visual or LADAR odometry is blocked by smoke or dust, and no longer seeing features, the position error will grow exponentially. This is due to the double integration errors, and the lack of other sensors contributing to the bias estimates.
The problems with localization become very evident on flying platforms, as they do not have wheel odometry to maintain the inertial biases. In small robotic platforms where the wheel slippage is large, the localization estimates also suffer accordingly.